Icinga Web 2 and all its modules have been localized from the very beginning. There were also quite a few languages added. Just recently Icinga Web 2 and the Director got a Japanese locale! And a updated Russian as well as a new Spanish (Argentina) locale are in the works at the moment. Over the years our Saudi Arabian, German, Finnish, Italian, Japanese, Brazilian, Russian and Ukrainian users were able to experience Icinga Web 2 and some of its modules in their native tongue.
While Google G Suite is an indispensable productivity and collaboration tool for modern businesses, all too frequently content tends to pile up in the far corners of Google Drive, making content search and discovery difficult. Spending valuable time sifting and searching through tens of thousands of documents to find the right one has become all too common, and most workers spend several hours per week searching for information.
Elasticsearch has a lot of strengths (speed, scale, relevance), but one of its most important strengths is its flexibility to be added to existing environments without the need for any sort of architectural overhaul. If you are a sysadmin (dev, sec, ops, etc.), you know just how appealing this is. So many legacy systems remain in place not because they are perfect, but because replacing them would cost time and money that you don't have.
Revenue monitoring not only involves monitoring huge amounts of data in real-time but also finding correlations between thousands, if not millions, of customer experience and other metrics. Are traditional monitoring methods capable of detecting a correlation between a drop in user log-ins and a drop in revenue as it’s happening? For many reasons, the answer is no.
We recently wrote about whether API Gateway can act as a Load Balancer. The answer is yes and, in many cases, they are substitutes for each other. But how should we choose which one to use? In this article, we will dive into more details on how these two types of HTTP networking services compare, using the AWS services as a base level: API Gateway and Application Load Balancer (ALB). Both are highly-scalable services to a point that scalability should not be a concern for most use cases.
Alert management is no longer a manageable task, given the growth in applications, cloud environments and point monitoring tools. Too much time is spent filtering and making sense of alert data and determining where to route incidents. All of these steps slow down critical issue identification and resolution. In this article, I want to discuss a more sensible, modern way to deal with IT alerts, through machine learning intelligence and automation.
It’s probably true to say that if you asked an average user what makes a great web application, they’d probably say “speed.” But speed is the probably the least important aspect of an extensive rundown of elements. Factors like application development and rendering in the program are probably higher on that list. And what makes up a great performing application? And when something goes wrong, how do you know?
Security is vital for protecting company assets and data subjects. Evolving data protection regulations, like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), have thrown light on security breaches and the security architecture of those compromised. In 2019, the global average cost for a data breach was $3.9 million, not including reputational damage and hidden costs.
I wanted to better understand how COVID-19 has been developing in South America. As I’ve recently started playing with InfluxDB, the open source time series database, I created a dashboard of cases and deaths using InfluxData’s platform. I usually use InfluxDB, Chronograf, Grafana, Zabbix and other similar solutions to monitor services and systems. However, until this point, I hadn’t used them to process and visualize other kinds of data.
